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Jurnal Sistem Teknik Industri
Published by Universitas Sumatera Utara
ISSN : 14115247     EISSN : 25279408     DOI : -
Core Subject : Science, Engineering,
Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering
Jurnal Sistem Teknik Industri (JSTI) of Universitas Sumatera Utara, Faculty of Engineering, Department of Industrial Engineering, was published in 1998. Until now, the number of publications has reached 21 volumes, each of which is published by TALENTA Publisher twice a year . Each volume has two publishing numbers, namely January issue numbers and July issue numbers.
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Articles 234 Documents
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Maintenance Analysis of Tension Measurement System on Cutter Machine Using Reliability Centered Maintenance (RCM) Dwi Nova Catharina Ramadhini Nainggolan; Asep Erik Nugraha; Wahyudin
Jurnal Sistem Teknik Industri Vol. 28 No. 3 (2026): JSTI Volume 28 Number 3 July 2026
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v28i3.25543

Abstract

PT XYZ is a manufacturing company in the paper industry with a continuous production system, making machine reliability a critical factor in maintaining smooth processes and high product quality. A vital system within the Cutter Strachain Henshain Machine (SHM) is the tension measurement system, which regulates paper web tension during the handling process. Field observations at PT XYZ revealed recurring disturbances caused by tension reading failure, which created significant discrepancies between Human Machine Interface (HMI) readouts and actual paper web conditions. While Reliability Centered Maintenance (RCM) is widely studied, its application to vintage, highly sensitive paper-tension control loops operating continuously for over two decades represents a distinct socio-technical operational gap. This study aims to analyze the maintenance strategy of the SHM tension measurement system using the RCM method to address this critical gap. Using a descriptive empirical approach incorporating structured observation, historical maintenance logging, and technical interviews, the system's operational functions, functional failure, and failure modes were systematically mapped. The analytical findings demonstrate that the primary point of failure stems from localized sensor contamination and localized degradation, severely compromising tension reading accuracy. Implementing an RCM-guided maintenance strategy, specifically through scheduled condition-directed maintenance and structured functional testing, is recommended. Quantitative projections indicate that these interventions can reduce total machine downtime by up to 15.4%, optimizing continuous production stability and mitigating cascading cutting defects.
A Literature Review: Particle Swarm Optimization (PSO) Algorithm for Scheduling Problems Shofiyyah Asrida; Juliza Hidayati; Rosnani Ginting
Jurnal Sistem Teknik Industri Vol. 28 No. 3 (2026): JSTI Volume 28 Number 3 July 2026
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v28i3.25584

Abstract

Scheduling is a fundamental combinatorial optimization problem that arises in numerous real-world domains, including manufacturing, cloud computing, healthcare, and transportation. Particle Swarm Optimization (PSO), inspired by the collective behaviour of bird flocking and fish schooling, has emerged as one of the most effective and widely applied metaheuristic approaches for solving scheduling problems. This systematic literature review synthesizes research published between 2004 and 2024, examining 35 peer-reviewed journal articles and conference papers to provide a comprehensive analysis of PSO applications, variants, and performance outcomes in scheduling. The review identifies key research trends, categorizes PSO variants, including Standard PSO, Hybrid PSO, Multi-Objective PSO, Adaptive PSO, and Quantum PSO, and evaluates their performance across different scheduling contexts. The findings indicate that Hybrid PSO approaches consistently outperform Standard PSO in terms of solution quality, while Adaptive PSO demonstrates superior convergence behaviour in dynamic environments. Current challenges, including premature convergence, scalability limitations, and parameter sensitivity, are highlighted alongside existing research gaps and potential directions for future research.
Literature Study on Analysis of Risky Riding Behavior in Motorcycle Riders Salsabila Sembiring; Nismah Panjaitan; Rosnani Ginting
Jurnal Sistem Teknik Industri Vol. 28 No. 3 (2026): JSTI Volume 28 Number 3 July 2026
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v28i3.25902

Abstract

Risky driving behavior among motorcyclists is one of the main factors contributing to the high traffic accident rates, especially in developing countries. This study aims to identify, analyze, and synthesize various factors influencing risky riding behavior among motorcyclists thru a Systematic Literature Review (SLR) approach. The research method was conducted by searching for scientific articles from various academic databases, such as Google Scholar, Scopus, and ScienceDirect, using keywords related to risky driving behavior, road safety, and motorcycle riders. The literature selection process was conducted based on inclusion and exclusion criteria to obtain relevant and high-quality articles. The study results show that risky driving behavior is influenced by several main factors, namely individual factors, psychological factors, environmental factors, and social and regulatory factors. The most frequently observed forms of risky behavior include speeding, using mobile phones while driving, not using personal protective equipment, running red lights, and aggressive behavior on the road. This study concludes that efforts to reduce risky driving behavior require a multidimensional approach thru safety education, consistent law enforcement, and the development of transportation policies focused on the safety of road users. This research is expected to serve as a foundation for the development of driving safety strategies and a reference for future studies.
A Generalized Eyring-Weibull Model for Degradation Analysis of Lithium-Ion Batteries Under Multi-Stressor Conditions Nur Faizatus Sa'idah; Hafidlotul Fatimah Ahmad
Jurnal Sistem Teknik Industri Vol. 28 No. 3 (2026): JSTI Volume 28 Number 3 July 2026
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v28i3.26011

Abstract

Degradation analysis of lithium-ion batteries is a critical aspect of understanding the aging behaviors and reliability of energy storage systems. Although purely data-driven approaches are widely utilized for their high short-term predictive accuracy, they often function as black-box models that fail to capture the underlying physicochemical mechanisms of capacity fade under dynamic operational conditions. To address these limitations, this study uses a Generalized Eyring-Weibull model for lithium-ion battery degradation analysis under multi-stressor conditions. The proposed analytical approach explicitly integrates three key operational stress variables simultaneously: temperature, State of Charge (SoC), and discharge current (C-rate). Model validation was performed using the NASA Prognostics Center of Excellence (PCoE) battery dataset across distinct discharge profiles (2A and 4A). Physical parameters—including activation energy (Ea) and stress exponents—were extracted via L-BFGS-B optimization, while the long-term capacity fade trajectory was tracked using Miner’s Rule. The evaluation results demonstrate that this generalized physics-based model accurately maps actual degradation trends, yielding high R2 values on State of Health (SoH) tracking. Furthermore, the model showcases superior robustness in capturing accelerated aging from high current loads using a single universal equation without requiring separate data retraining. By bridging empirical data with fundamental kinetic principles, this study provides an interpretable and robust analytical methodology for advanced predictive maintenance strategies.

Page 24 of 24 | Total Record : 234

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